Assessing the potato yield gap in the Peruvian Central Andes

D. Grados, S. García and E. Schrevens

Agricultural Systems, 2020, vol. 181, issue C

Abstract: The Peruvian Central Andes is a highly important area for potato production. Assessing the potato yield gap and the potential yield is an essential step towards sustainable crop intensification. Fifty-eight smallholder potato farmer's plots in total were monitored at field level during the 2005–2008 and 2010–2015 rainy cropping seasons. All the main crop management inputs were registered. Three field experiments (on-farm trials) established during the 2014–2017 rainy cropping seasons were used to calibrate (2014–2016) and validate (2016–2017) the SUBSTOR-potato model under potential conditions. Potential potato yield (Yp) was estimated for each individual field pilot plot (in kg ha−1) based on the calibrated and validated crop model. Yield gaps (Yg) were calculated as the difference between Yp and farmers' actual yield (Ya). A classification tree-based model predicting the potato gap quantiles was used to elucidate the main biophysical and crop management components inducing Yg.

Keywords: Potential yield; farmers' yield; SUBSTOR-potato model; Gap assessment; Classification tree; Cropping systems (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0308521X1930575X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:agisys:v:181:y:2020:i:c:s0308521x1930575x

DOI: 10.1016/j.agsy.2020.102817

Access Statistics for this article

Agricultural Systems is currently edited by J.W. Hansen, P.K. Thornton and P.B.M. Berentsen

More articles in Agricultural Systems from Elsevier
Bibliographic data for series maintained by Catherine Liu ().